Semantic Grounding Strategies for Tagbased Recommender Systems
Semantic locations – personal web recommender
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Transcript of Semantic locations – personal web recommender
Semantic Locations – Personal Web Recommender
Diana Amitroaei, Stefan Orzu Leon, George Rosca, Lenuta Alboaie1 UAIC: Faculty of Computer Science, “Alexandru Ioan Cuza” University, Romania{diana.amitroaei, stefan.orzu, george.rosca, adria}@info.uaic.ro
Objective
Give for each user recommendation of places like:
• gas stations• restaurants• banks• schools etc.
based on location and his unique user identifier along with stored preferences in an intelligent way
Application – user flow
The application consists of three big modules:
• the client application
• the server application
• the protocol module (which was implemented from scratch
using sockets)
Communication protocol
• contains the common classes passed between the client and the server:
▪ LocationObject ▪ Place
▪ User ▪ Message
• • contains the implementation of the client connection and also the Message class and the Receiver interface
Application server
• plugin-able
• multithreaded
public interface PerePlugin { public ArrayList<Place> getPlaces(User user); public ArrayList<User> getUsers(User user); public void updateUser(User user);}
Application client
is written in Java using the Android SDK the user location is retrieved using:
▪ GPS satellites
▪ Wireless networks triangulation
methods
Application technologies
• Android
• RDF using Jena
• Google API (Google Places & Google Maps)
• Google Places API
Application technologies
• Android
• RDF using Jena
• Google API (Google Places & Google Maps)
• Google Places API
Installation
The user is being prompted with the client application’s permissions required:
• Network Communication
• Coarse locations/fine locations
• Modify/delete USB storage content
Installation screen
Page wizard
The main screen of the application has two parts:
Simple UI
Advance UI
Multumim!